Using automated detection and response technology mitigate the next Corona pandemic

What happens the day after?   What happens next winter?

Sure – we must find effective treatment and vaccines.  Sure – we need  to reduce or eliminate the need for on-site monitoring visits to hospitals in clinical trials.  And sure – we need to enable patient monitoring at home.

But let’s not be distracted from 3 more significant challenges:

1 – Improve patient care

2 – Enable real-time data sharing. Enable participants in the battle with COVID-19 to share real-world / placebo arm data, making the fight with COVID-19 more efficient and collaborative.

3- Enable researchers to dramatically improve data reliability, allowing better decision making and improving patient safety.

Clinical research should ultimately improve patient care.

The digital health space is highly fragmented (I challenge you to precisely define the difference between patient engagement apps and patient adherence apps and patient management apps).  There are over 300 digital therapeutic startups. We are lacking a  common ‘operating system and  there is a dearth of vendor-neutral standards that would enable interoperability between different digital health systems mobile apps and services.

By comparison – clinical trials have a well-defined methodology, standards (GCP) and generally accepted data structures in case report forms.  So why do many clinical trials fail to translate into patient benefit?

A 2017 article by Carl Heneghan, Ben Goldacre & Kamal R. Mahtani “Why clinical trial outcomes fail to translate into benefits for patients”  (you can read the Open Access article here) states the obvious: that the objective of clinical trials is to improve patients’ health.

The article points at  a number of serious  issues ranging from badly chosen outcomes, composite outcomes, subjective outcomes and lack of relevance to patients and decision makers to issues with data collection and study monitoring.

Clinical research should ultimately improve patient care. For this to be possible, trials must evaluate outcomes that genuinely reflect real-world settings and concerns. However, many trials continue to measure and report outcomes that fall short of this clear requirement…

Trial outcomes can be developed with patients in mind, however, and can be reported completely, transparently and competently. Clinicians, patients, researchers and those who pay for health services are entitled to demand reliable evidence demonstrating whether interventions improve patient-relevant clinical outcomes.

There can be fundamental issues with study design and how outcomes are reported.

This is an area where modeling and ethical conduct intersect;  both are 2 critical areas.

Technology can support modeling using model verification techniques (used in software engineering, chip design, aircraft and automotive design).

However, ethical conduct is still a human attribute that can neither be automated nor replaced with an AI.

Let’s leave modeling to the AI researchers and ethics to the bioethics professionals

For now at least.

In this article, I will take a closer look at 3 activities that have a crucial impact on data quality and patient safety. These 3 activities are orthogonal to the study model and ethical conduct of the researchers:

1 – The time it takes to detect and log protocol deviations.

2 – Signal detection of adverse events (related to 1)

3 – Patients lost to follow-up (also related to 1)

Time to detect and log deviations

The standard for study monitors is to visit investigational sites once ever 5-12 weeks.   A Phase IIB study with 150 patients that lasts 12 months would typically have 6-8 site visits (which incidentally, cost the sponsor $6-8M including the rewrites, reviews and data management loops to close queries).

Adverse events

As reported by Heneghan et al:

A further review of 11 studies comparing adverse events in published and unpublished documents reported that 43% to 100% (median 64%) of adverse events (including outcomes such as death or suicide) were missed when journal publications were solely relied on [45]. Researchers in multiple studies have found that journal publications under-report side effects and therefore exaggerate treatment benefits when compared with more complete information presented in clinical study reports [46]

Loss of statistical significance due to patients lost to follow-up

As reported by Akl et al in  “Potential impact on estimated treatment effects of information lost to follow-up in randomized controlled trials (LOST-IT): systematic review” (you can see the article here):

When we varied assumptions about loss to follow-up, results of 19% of trials were no longer significant if we assumed no participants lost to follow-up had the event of interest, 17% if we assumed that all participants lost to follow-up had the event, and 58% if we assumed a worst case scenario (all participants lost to follow-up in the treatment group and none of those in the control group had the event).

Real-time data

Real-time data (not data collected from paper forms 5 days after the patient left the clinic) is key to providing an immediate picture and assuring interpretable data for decision-making.

Any combination of data sources should work – patients, sites, devices, electronic medical record systems, laboratory information systems or some of your own code. Like this:

Mobile eSource mobile ePRO medical device API

Signal detection

The second missing piece is signal detection for safety, data quality and risk assessment of patient, site and study,

Signal detection should be based upon the clinical protocol and be able to classify the patient into 1 of 3 states: complies, exception (took too much or too little or too late for example) and miss (missed treatment or missing data for example).

You can visualize signal classification as putting the patient state into 1 of 3 boxes like this:Automated response

One of the biggest challenges for sponsors running clinical trials is delayed detection and response.   Protocol deviations are logged 5-12 weeks (and in a best case 2-3 days) after the fact.   Response then trickles back to the site and to the sponsor – resulting in patients lost to follow-up and adverse events that were recorded long after the fact..

If we can automate signal detection then we can also automate response and then begin to understand the causes of the deviations.    Understanding context and cause is much easier when done in real-time.        A good way to illustrate is to think about what you were doing today 2 weeks ago and try and connect that with a dry cough, light fever and aching back.   The symptoms may be indicative of COVID-19 but y0u probably don’t remember what you were doing and  with whom you came into close contact.     The solution to COVID-19 back-tracking is use of digital surveillance and automation. Similarly, the solution for responding to exceptions and misses is to digitize and automate the process.

Like this:

Causal flows of patient adherence

Summary

In summary we see 3 key issues with creating meaningful outcomes for patients:

1 – The time it takes to detect and log protocol deviations.

2 – Signal detection of adverse events and risk (related to 1)

3 – Patients lost to follow-up (also related to 1)

These 3 issues for creating meaningful outcomes for patients can be resolved with 3 tightly integrated technologies:

1 – Real-time data acquisition for patients, devices and sites (study nurses, site coordinators, physicians)

2 – Automated detection

3 – Automated response

 

 

 

 

Temperature excursions and APIs to reduce study monitor work

I did a lot of local excursions the past 3 days – Jerusalem, Tel Aviv, Herzliya and Haifa.   For some reason, the conversations with 2 prospects had to do with refrigerators.   I do not know if this is Freudian or not, considering the hot weather of July in Israel.

The conversations about refrigerators had to do with storing drugs / investigational product at the proper temperatures.

Temperature excursion is a deviation

The great thing about not coming from the clinical trials space is that you are always learning new things.

Yesterday – I learned that a Temperature excursion is a deviation from given instructions. It is defined in the WHO Model Guidance as “an excursion event in which a Time Temperature Sensitive Pharmaceutical Product (TTSPP) is exposed to temperatures outside the range(s) prescribed for storage and/or transport.

Storing drugs at the proper temperature is part of GCP. Here is an SOP for Monitoring and Recording Refrigerator & Freezer Temperatures

1 Introduction All refrigerators and freezers used for the storage of Investigational Medicinal Products (IMPs) must be temperature controlled, and continuously monitored and maintained within the appropriate ranges as defined by the protocol. ICH GCP Principle 2.13 states “Systems with procedures that assure the quality of every aspect of the trial should be implemented.”

Moving on:

5 Procedure
 Current maximum/minimum thermometers must be monitored as a minimum at least once on a daily basis on all working days, and recorded legibly on the temperature monitoring log.
 The digital maximum/minimum thermometer –
□ Should be read from the outside of the refrigerator without opening the door.
□ Have an accuracy of at least +/- 1 oC.
□ Be able to record temperatures to one decimal place.
□ Be supplied with a calibration certificate.
□ Have the calibration check on an annual basis.
 Temperature logs should be kept close to the refrigerator/freezer (but not inside) to which they relate for ease of reference, and should be clearly identified as relating to that appliance.
 A separate temperature record must be kept for each fridge/freezer. (The use of whiteboards as a method of logging results is not acceptable.)
 It is good practice to record the temperature at a similar time each day e.g., first thing in the morning before the refrigerator door is opened for the first time. This will allow review of trends in results recorded; help highlight any changes in temperatures recorded and deviation in refrigerator performance.

There is a lot of manual work involved looking at refrigerators

I believe a study monitor will spend 20’/day checking logs of refrigerator temperature readings. When you add in time for data entry to the site coordinators – that’s another 20’/day and then you have to multiply by the number of sites and refrigerators.   This is only the reading temperatures and capturing data to the EDC part of the job.   Then you have to deal with queries and resolving deviations.

For something so mundane (although crucial from a medical research perspective), its a lot of work. The big problem with using study monitors to follow temperature excursions is that the site visits are every 1-3 months. With the spiralling costs of people, the site visits are getting less frequent.

This means that it is entirely plausible that patients are treated with improperly stored drugs and the deviation is undetected for 3 months.

Whenever I see a lot of manual work and late event detection, I see an opportunity.

It seems that there are a few vendors doing remote monitoring of refrigerators.  A Polish company from Krakow, called Efento has a complete solution for remote monitoring of refrigerators storing investigational product.  It looks like this:

 

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What is cool (to coin a pun) about Efento is that they provide a complete solution from hardware to cloud.

The only thing missing is calling a Flask API to insert data into the eCRF for the temperature excursions.

Once’s we’ve got that, we have saved all of the study coordinators and study monitors time.

More importantly, we’ve automated an important piece of the compliance monitoring puzzle – ensuring that temperature excursions are detected and remediated immediately before its too late.

Doctor-Patient Communication – the key to success and the struggle to succeed.

Katherine Murphy, Chief Executive of the Patients Association London once said,

“The huge rise in complaints in relation to communication and a lack of respect are of particular concern. Patients are not receiving the compassion, dignity and respect which they deserve.”

As clinical trial technology guys, you would assume that we love code more than we love the patients and site coordinators who use our software.

I took a random sample of  home pages from 3 of our competitors – and this is what I found.   We can discuss if real-time visibility to  data is going to make the clinical operations team more effective or not – but that is a story for another post.

EMPOWER YOUR CLINICAL TRIAL EDC + ePRO and a bunch of other features to make your clinical trial successful. ( viedoc )

Oracle Health Sciences InForm. Accelerate Clinical Trial Timelines While Reducing Trial Cost and Risk.

Collect and deliver higher-quality data faster through advanced data capture and query management, real-time visibility to data, standards-based, integrated workflows, and security best practices.

Faster, smarter medical research. Castor is the end-to-end data solution, enabling researchers to easily capture and integrate data from any source on one platform. Thousands of medical device, biotech, and academic researchers around the world are using Castor EDC (Electronic Data Capture), ePRO, and eTMF to accelerate their studies.

In this article we’ll discuss the doctor-patient communications gap as a generic problem. We will briefly examine the root cause of the problem and conclude by proposing a light-weight easy-to-use Web service for sharing and private messaging with patients and physicians as a way to ameliorate the problem.

Poor patient-doctor communications as a generic problem

Doctor-Patient communication is the key to the success of a treatment plan and reduction of hospital readmission. However, doctors and nurses often fail in communicating with their patients properly.

What is the nature of poor doctor-patient communications?

Some patients say that their doctors need to polish their communication skills; although they are excellent diagnosticians.

Other patients say that their doctors know how to talk, but seem to have no time to listen.

Many patients also complain that their doctors don’t explain things in terms patients can understand. Poor communications between doctors/nurses and their patients can come at a high cost, creating misunderstandings that can  lead to malpractice suits.

In a hospital setting, we often hear that patients feel that they are not getting any useful information while the medical staff feel that they have taken the time to communicate all the data that the patients and their families need in order to understand and comply with the treatment plan.

The question is why some doctors find it hard to communicate properly and share things with their patients in a desired manner while other doctors succeed in communicating the therapeutic plan to the patient in a manner that the patient understands.

Poor physician-patient communications is rooted in cognitive and cultural gaps

Patients are the experts at their personal feelings and experiences.  Physicians are the experts in the medical science.  Cultural and language differences and preconceived notions about the doctors role only contribute to the cognitive gap between emotion and science.

Besides the cultural and cognitive gaps, high patient volume and work overload is another root contributor to poor doctor patient communications.  This generally happens in poor countries. In the third world, working over capacity is one of the biggest barriers to effective communication. Hospitals, doctors and nurses are forced to admit more and more patients and are compelled to handle more than they can manage. Under such circumstances, health professionals cannot devote enough time to their patients let alone sit down with them in a quiet corner and explain the therapeutic plan.

Sharing and private messaging with patients  and doctors helps bridge the gaps

The solutions are out there.

In this always-on age of mobile medical devices and cloud services, both healthcare professionals and the patients have immediate access to the latest solutions that can help them communicate more effectively and efficiently. There are private social networks for healthcare that have been exclusively developed for sharing and private messaging with doctors, nurses and patients, enabling doctors and patients to interact and share where and whenever they need the interaction.

Neither the patient nor the physician need to be tied down to a proprietary healthcare provider portal.

Secure Web-based sharing and private messaging services improve the ways doctors and nurses communicate with their patients. This helps them improve the quality of service and lower operational costs, and enables doctors to treat more patients in less time and with less stress.

In summary

Poor patient-doctor communications has a number of causes and it is rooted in both cultural, language and cognitive differences.   Using a neutral medium such as online sharing and private messaging with patients and doctors helps bridge the gaps we discussed.

We’d love to hear what you think – please comment!

Thanks!

Urban medical legends

Because I was trained as a solid-state physicist I am skeptical of many medical claims – including the efficacy of digital health apps.  Gina Kolata wrote this post last week.  I’ll let you decide for yourself.

You might assume that standard medical advice was supported by mounds of scientific research. But researchers recently discovered that nearly 400 routine practices were flatly contradicted by studies published in leading journals.

 

(more…)

Why Microsoft is evil for medical devices

Another hot day in paradise. Sunny and 34C.

Not a disaster but still a PITA

We just spent 2 days bug-fixing and regression-testing code that was broken by Microsoft’s June security update to Windows operating systems and Explorer 11.    Most of the customers of the FlaskData EDC, ePRO, eSource and automated detection and response platform use Chrome or Firefox on their desktops.   This was no solace to site coordinators in one of the sites using Flaskdata.  They came into work on Monday and the hospital-standard Explorer 11 no longer supported our application.

Microsoft published KB4503259 as a cumulative security update but it was much more.  The update included major changes to the Explorer JavaScript engine. Its because of delightful black swans like this, running a SaaS business is not for the faint of heart.

I once wrote an essay on my cybersecurity for medical device blog called The Microsoft Monoculture as a threat to national security.

Why Microsoft is evil for medical devices

I suggested that the FDA might consider banning Windows as an operating system platform for medical devices and their accompanying information management systems.

One of my readers took umbrage at the notion of legislating one monoculture (Microsoft) with another (Linux) and how the Linux geeks are hooked on the CLI just like Windows users are hooked on a GUI.

The combination of large numbers of software vulnerabilities,  user lock in created by integrating applications with Windows,  complexity of Microsoft products and their code and Microsoft predatory trade practices are diametrically different than Linux and the FOSS movement.

The biggest threats to medical devices in hospitals is old Windows versions

One of the biggest threats to medical devices in hospitals is the widespread use of USB flash disk drives and Windows notebooks to update medical device software. With the infamous auto-run feature on Microsoft USB drives – flash memory is an easy attack vector for propagating malware via Windows based medical devices into a hospital network. This is one (and not the only) reason, why I am campaigning against use of Windows in medical devices.

This  has nothing to do with the CLI or GUI of the operating system and personal preferences for a user interface.

This has everything to do with manufacturing secure embedded medical devices that must survive in most demanding, heterogeneous and mission critical environment one can imagine – a modern hospital.

I never advocated mandating Linux by law for medical devices.

It might be possible to mandate a complex set of software security requirements instead of outlawing Windows in embedded medical devices as a more politically-correct but far more costly alternative for the the FDA and the US taxpayer.

Regardless of the politics involved (and they are huge…) – if the FDA were to remove Windows from an approved list of embedded medical device operating systems – the costs to the FDA would decrease since the FDA would need less Windows expertise for audits and the threat surface they would have to cover for critical events would be smaller.

Obsessed with patient compliance

Obsessed with patient compliance

I’m watching a series of short videos done by Techstars founder Brad Feld.

Brad talks about founders needing to be obsessive.

I am totally obsessed with patient compliance.

The key to speed in medical device trials is eliminating non-value-added activities and automating everything else.

There are a lot of smart people working on RWD and RWE and mobile, AI and machine learning.

We are working on automating patient compliance detection and response because we are obsessed with making site coordinators more productive.

We correlate 3 streams of data: patient, device and site coordinator and automated detection and response of patient compliance deviations and then apply some decision trees.

In order to catch high-priority events (like over or under-dosing), the study team can subscribe to real-time alerts.

The patients can be subscribed to adaptive reinforcement messages.

The site coordinator, study monitors and project manger get real-time analytics showing trends of patient compliance sliced and diced by patient, site, cohort, date, time…

So far – the results with customers have been encouraging – with our early adopters achieving 85-95% patient compliance in global multi-centre studies.

Check out my colleague Tigran’s post on the absurd idea of using edit checks to assure patient compliance.

How to improve patient compliance in your medical device study

Here’s an idea that will make you slap your forehead.

You can just stop transcribing case reports on paper.

FDA eSource guidance recommends direct data entry into your EDC.  The eCRF becomes electronic source and you eliminate source document verification.

You save money, systems, time and you get to go home early.

Don’t let people confuse you with all kinds of complicated scenarios just because they’re selling systems.

Check out my blog post on Why merging medical records and clinical trial data is a very bad idea and see how merging EMR and clinical trial data can expose you to data breaches and endanger your clinical trial success.

Just keep it simple.

Do you  have 15 minutes for a quick call  with me?

– Tuesday @10 AM
– Wed @ 12AM
– Thur @ 2PM
Schedule a call with me  https://calendly.com/dannyl/15min

Killed by code in your connected medical device

patient compliance in medical clinical device trials

Are we more concerned with politicians with pacemakers or families with large numbers of connected medical devices?

Back in 2011, I thought it would only be a question of time before we have a drive by execution of a politician with an ICD (implanted cardiac device). May 2019, with mushrooming growth in connected medical devices (and after the Israeli 2019 elections), I am rethinking my risk analysis.

Consider this: If a typical family of 2 parents and 3 children have 5 mobile devices, it is a reasonable that this number will double with medical IoT and software as devices for diabetes management, asthma monitoring, fetal monitoring, remote diagnosis of children, home-based urine testing and more.

So far, it seems the politicians are still around, but the cybersecurity vulnerabilities for medical devices are growing in frequency and impacting big medical device vendors like Medtronic as reported by FDA in March 2019 – Cybersecurity Vulnerabilities Affecting Medtronic Implantable Cardiac Devices, Programmers, and Home Monitors

Audience: Patients with a Medtronic cardiac implantable cardioverter defibrillators (ICDs) or cardiac resynchronization therapy defibrillators (CRT-Ds)

-Caregivers of patients with a Medtronic ICD or CRT-D

-Cardiologists, electrophysiologists, cardiac surgeons, and primary care physicians treating or managing patients with heart failure or heart rhythm problems using a Medtronic ICD or CRT-D

-Medical Specialties

-Cardiac Electrophysiology, Cardiology, Cardiothoracic Surgery, Heart Failure

Purpose: The U.S. Food and Drug Administration (FDA) is issuing this safety communication to alert health care providers and patients about cybersecurity vulnerabilities identified in a wireless telemetry technology used for communication between Medtronic’s implantable cardiac devices, clinic programmers, and home monitors. The FDA recommends that health care providers and patients continue to use these devices as intended and follow device labeling.

Although the system’s overall design features help safeguard patients, Medtronic is developing updates to further mitigate these cybersecurity vulnerabilities. To date, the FDA is not aware of any reports of patient harm related to these cybersecurity vulnerabilities.

In Jan 9, 2017 FDA reported in a FDA Safety Communication on “Cybersecurity Vulnerabilities Identified in St. Jude Medical’s Implantable Cardiac Devices and Merlin@home Transmitter.

At risk:

-Patients with a radio frequency (RF)-enabled St. Jude Medical implantable cardiac device and corresponding Merlin@home Transmitter

-Caregivers of patients with an RF-enabled St. Jude Medical implantable cardiac device and corresponding Merlin@home Transmitter

-Cardiologists, electrophysiologists, cardiothoracic surgeons, and primary care physicians treating patients with heart failure or heart rhythm problems using an RF-enabled St. Jude Medical implantable cardiac device and corresponding Merlin@home Transmitter

Different classes of device. Different threat scenarios. A wellness app does not have the same threat model as implanted devices

I’ve been talking to our medical device customers about mobile security of implanted devices for over 7 years now.

I  gave a talk on mobile medical device security at the Logtel Mobile security conference in Herzliya in 2012 and discussed proof of concept attacks on implanted cardiac devices with mobile connectivity.

But – ICD are the edge, the corner case of mobile medical devices.

If a typical family of 2 parents and 3 children have 5 mobile devices, it is a reasonable scenario that this number will double withe devices for fetal monitoring, remote diagnosis of children, home-based urine testing and more.

Mobile medical devices are becoming a pervasive part of the Internet of things; a space of  devices that already outnumber workstations on the Internet by about five to one, representing a $900 billion market that’s growing twice as fast as the PC market.

There are 3 dimensions to medical device security – regulatory (FDA), political (Congress) and cyber (vendors implementing the right cyber security countermeasures)

The FDA is taking a tailored, risk-based approach that focuses on the small subset of mobile apps that meet the regulatory definition of “device” and that the software as a device mobile apps:

-are intended to be used as an accessory to a regulated medical device, or

-transform a mobile platform into a regulated medical device.

Mobile apps span a wide range of health functions. While many mobile apps carry minimal risk, those that can pose a greater risk to patients will require FDA review. The FDA guidance document  provides examples of how the FDA might regulate certain moderate-risk (Class II) and high-risk (Class III) mobile medical apps. The guidance also provides examples of mobile apps that are not medical devices, mobile apps that the FDA intends to exercise enforcement discretion and mobile medical apps that the FDA will regulate in Appendix AAppendix B and Appendix C.

Mobile and medical and regulatory is a pretty sexy area and I’m not surprised that politicians are picking up on the issues. After all, there was an episode of CSI New York  that used the concept of an EMP to kill a person with an ICD, although I imagine that a radio exploit of  an ICD or embedded insulin pump might be hard to identify unless the device itself was logging external commands.

See my presentation ‘Killed by code’

Congress is I believe, more concerned about the regulatory issues than the patient safety and security issues:

Representatives Anna Eshoo (D-CA) and Ed Markey (D-MA), both members of the House Energy and Commerce Committee sent a letter last August asking the GAO to Study Safety, Reliability of Wireless Healthcare Tech and report on the extent to which FCC is:

Identifying the challenges and risks posed by the proliferation of medical implants and other devices that make use of broadband and wireless technology.
Taking steps to improve the efficiency of the regulatory processes applicable to broadband and wireless enabled medical devices.
Ensuring wireless enabled medical devices will not cause harmful interference to other equipment.
Overseeing such devices to ensure they are safe, reliable, and secure.Coordinating its activities with the Food and Drug Administration.

At  Black Hat August 2011, researcher Jay Radcliffe, who is also a diabetic, reported how he used his own equipment to show how attackers could compromise instructions to wireless insulin pumps.

Radcliffe found that his monitor had no verification of the remote signal. Worse, the pump broadcasts its unique ID so he was able to send the device a command that put it into SUSPEND mode (a DoS attack). That meant Radcliffe could overwrite the device configurations to inject more insulin. With insulin, you cannot remove it from the body (unless he drinks a sugary food).

The FDA position that it is sufficient for them to warn medical device makers that they are responsible for updating equipment after it’s sold and the downplaying of  the threat by industry groups like The Advanced Medical Technology Association is not constructive.

Following the proof of concept attack on ICDs by Daniel Halperin from the University of Washington, Kevin Fu from U. Mass Amherst et al “Pacemakers and Implantable Cardiac Defibrillators:Software Radio Attacks and Zero-Power Defenses”  this is a strident wakeup call to medical device vendors  to  implement more robust protocols  and tighten up software security of their devices.

Living off generic solutions developed in the past

I recently read some posts on Fred Wilson’s blog and it was impressive that he writes every day.

I’ve fallen into the trap of collecting raw material and then waiting to find time to write a 2000-word essay on some topic of importance to me.   But, I think it was Steve Jobs who said the best time to do anything was 20 years ago and failing that – best time is now.  So now – I will start writing every day and attempt to write on topics of interest to my customers, not me.

We are working on automating patient compliance in medical device clinical trials.   Patient compliance is critical for the success of medical device studies.

When we mean success – we mean proving or disproving the scientific hypothesis of the study.  Efficacy – is the device an effective treatment for the indication?

Safety – is the device safe for patients?

When we say patient compliance automation we mean the combination of 4 things which depend on each other:

1.Reinforcing patient compliance to the protocol – for example reporting on time and taking the treatment on time.  AI-based reinforcement uses data from the patient’s behavior and similar behavior to keep the patient on track without driving him crazy with text or push messaging.

2.Automated monitoring of compliance – using clinical measures and the treatment schedule for the study.    An example of a clinical measure is the number of capsules a patient took. An example of treatment schedule is taking the capsules every day before 12.

The output of automated monitoring is real-time alerts and compliance trends to the study team.

3. Automate patient compliance reinforcement using and adaptive control process that takes fresh data from the alerts to make decisions on how to reinforce the patient and keep them on track.

4.In order to automate monitoring and do AI-based reinforcement of patient compliance, you need fresh and up-to-date data.

There is a lot of work being done by startups like Medable, Litmus Health and Flaskdata.io (disclaimer – I am the founder of Flaskdata.io) but it’s a drop in the ocean of 24,000 new clinical trials every year.

Fundamentally – the problem is that the clinical trials industry uses generic solutions developed 40 years ago to assure quality of data-entry from paper forms.

The generic solution used today involves waiting 1-3 days for site data collection to the EDC, and 4-6 weeks for a site visit and SDV and then another 1-12 weeks for a central monitoring operation in your CRO to decide that there was a protocol violation.

You don’t have to be a PhD data scientist to understand that you cannot assure patient compliance to the clinical protocol with 12-week-old data.

The only explanation for using 40-year-old generic solutions is that the CRO business model is based on maximizing billable hours instead of maximizing patient compliance.

It seems that if you want to achieve real-time detection and response and AI-based patient compliance reinforcement, you have to disrupt the CRO business model first.

Invisible gorillas and detection of adverse events in medical device trials

Weekly Episode #1 - Patients and study monitors are both people.

What is easier to detect in your study – Slow-moving or fast moving deviations?

This post considers human frailty and strengths.

We recently performed a retrospective study of the efficacy of  Flaskdata.io automated study monitoring in orthopedic trials. An important consideration was the ability to monitor patients who had received an implant and were on a long term follow-up program. Conceptually, monitoring small numbers of slow-moving, high-risk events is almost impossible to do manually since we miss a lot of what goes on around us, and we have no idea that we are missing so much. See the invisible gorilla experiment for an example.

One of patients in the study had received a spinal implant and was on a 6 month follow-up program dived into a pool to swim a few laps and died by drowning despite being a strong swimmer. Apparently, the pain caused by movement of the insert resulted  in loss of control and a severe adverse event. The patient had disregarded instructions regarding strenuous physical activity and the results were disastrous. 

It seems to me that better communications with the patients in the medical device study could have improved their level of awareness of safety and risk and perhaps avoided an unnecessary and tragic event.

Subjects and study monitors are both  people.

This might be a trivial observation but I am going to say it anyhow, because there are lessons to be learned by framing patients and monitors as people instead of investigation subjects and process managers. 

People are the specialists in their personal experience, the clinical operations team are the specialists in the clinical trial protocol. Let’s not forget that subjects and study monitors are both  people.

Relating to patients in a blinded study as subjects without feelings or experience is problematic. We can relate to patients in a personal way without breaking the double blinding and improve their therapeutic experience and their safety. 

We should relate to study monitors in a personal way as well, by providing them with great tools for remote monitoring and enable them to prioritize their time on important areas such as dosing violations and sites that need more training. We can use analytics of online data from the EDC, ePRO and eSource and connected medical devices in order to enhance and better utilize clinical operations teams’ expertise in process and procedure.

A ‘patient-centered’ approach to medical device clinical trials

In conditions such as Parkinsons Disease, support group meetings and online sharing are used to stay on top of medication, side effects, falls and general feeling of the patient even though the decisions on the treatment plan need to be made by an expert neurologist / principal investigator and oversight of protocol violations and adverse events is performed by the clinical operations team. There are many medical conditions where patients can benefit by taking a more involved role in the study. One common example is carpal tunnel syndrome. 

According to the findings of an August 3rd, 2011 issue of the Journal of Bone and Joint Surgery (JBJS), patients receiving treatment for carpal tunnel syndrome (CTS) prefer to play a more collaborative role when it comes to making decisions about their medical or surgical care. 

Treatment of carpal-tunnel syndrome which is very common and also extremely dependent upon patient behavior and compliance is a great example of the effectiveness of “shared decision-making, or collaborative, model” in medicine, in which the physician and patient make the decision together and exchange medical and other information related to the patient’s health.

As the article in JBJS concludes:

“This study shows the majority of patients wanted to share decision-making with their physicians, and patients should feel comfortable asking questions and expressing their preferences regarding care. Patient-centered care emphasizes the incorporation of individual styles of decision making to provide a more patient-centered consultation,” Dr. Gong added. 

In a ‘patient-centered’ approach to medical device clinical trials, patients’ cultural traditions, personal preferences and values, family situations, social circumstances and lifestyles are considered in the decision-making process.

Automated patient compliance monitoring with tools such as Flaskdata.io are a great way to create a feedback loop of medical device clinical data collection,  risk signatures improvement, detection of critical signals and communications of information to patients. Conversely, automated real-time patient compliance monitoring is a a great way of enhancing clinical operations team expertise.

Patients and study monitors are both people.